Full Stack Data Scientist

Role Description

We are seeking a highly skilled and innovative Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering, with a focus on developing end-to-end data-driven solutions. This role offers an exciting opportunity to leverage advanced analytics and cutting-edge technologies to drive impactful business outcomes. This is a Remote position.

• Data Collection and Preprocessing:
  • Develop robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from various sources.
  • Implement strategies for data quality assessment and assurance to ensure reliable analysis outcomes.
• Exploratory Data Analysis and Visualization:
  • Conduct comprehensive exploratory data analysis to uncover patterns, trends, and insights within the data.
  • Create interactive visualizations and dashboards to effectively communicate findings to stakeholders.
• Machine Learning Model Development:
  • Design, develop, and deploy predictive models using advanced machine learning algorithms and techniques.
  • Optimize model performance through feature engineering, hyperparameter tuning, and model selection.
• Software Development and Integration:
  • Build scalable and efficient software solutions for deploying machine learning models into production environments.
  • Integrate data science workflows with existing systems and applications to enable seamless data-driven decision-making.
• Performance Monitoring and Maintenance:
  • Establish monitoring mechanisms to track the performance of deployed models and identify opportunities for improvement.
  • Conduct regular maintenance activities to ensure the reliability, stability, and scalability of data science solutions.
• Collaboration and Cross-functional Communication:
  • Collaborate closely with cross-functional teams including data engineers, software developers, and business stakeholders.
  • Communicate technical concepts and findings effectively to both technical and non-technical audiences.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• Proven experience in data preprocessing, exploratory data analysis, and feature engineering.
• Expert-level skills in data visualization platforms (e.g. Qlik, Tableau, Power BI).
• Proficiency in programming languages such as Python, R, and SQL for data manipulation and analysis.
• Strong understanding of machine learning algorithms and statistical modeling techniques.
• Hands-on experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
• Experience in developing and deploying end-to-end data science solutions in cloud environments (e.g., AWS, Azure, GCP).
• Solid understanding of software engineering principles and best practices for building scalable and maintainable code.

Preferred Qualifications

• Experience building solutions for Commercial clients in Pharma, Biotech, CPG, Retail or Manufacturing industries.
• Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Knowledge of DevOps practices for continuous integration and deployment (CI/CD).
• Experience with distributed computing frameworks for parallel processing (e.g., Dask, Ray).
• Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.

Company Description

Driven by Innovation and built on Trust, rockITdata is a unique SDVOSB services company that partners with leading commercial healthcare/life sciences organizations on cutting edge innovations - think AI, automation and data transformation. We then bring those commercially tested solutions to government entities to deliver predictable, measurable impact for the American taxpayer and consumer.